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Download JNTUA MBA 2017 Nov 3rd Sem 14E00319 Data Warehousing & Mining Question Paper

Download JNTU Anantapur (Jawaharlal Nehru Technological University Anantapuramu) MBA 2017 November Third Semester (3rd Semester/1-2) Regular & Supplementary Examinations 14E00319 Data Warehousing & Mining Question Paper.

This post was last modified on 03 January 2020

JNTU Anantapur MBA 3rd Sem last 10 year question papers 2010 -2020 -All regulation- 2nd Year 1st Sem


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Code: 14E00319

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MBA III Semester Regular & Supplementary Examinations November/December 2017

DATA WAREHOUSING & MINING

(For students admitted in 2014, 2015 & 2016 only)

Time: 3 hours

Max. Marks: 60

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PART - A

(Answer the following: (05 X 10 = 50 Marks)


  1. How can you evaluate database technology?

    OR

    Explain how to organize the data warehousing in data management.
  2. Explain the data sharing between functional units and different levels of users.

    OR

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    Explain database system in data warehousing.
  3. (a) Explain how a relational database can be organized for a data warehouse.
    (b) Explain four levels of data in data warehouse environment with example.

    OR

    (a) What is data cleaning? Why is it necessary?
    (b) How to choose the right database structure for a data warehouse? Explain.
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  5. What are the four types of data that the data warehouse architecture must specify? Explain.

    OR

    (a) What are the three basic elements of a project plan?
    (b) Explain how a OLAP analysis might proceed.
  6. What is data cleaning? Why is it necessary?

    OR

    What situation, where data transformation would be necessary in preparing data to be loaded into a data warehouse?
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PART - B

(Compulsory question, 01 X 10 = 10 Marks)

Case study:

You have decided to prepare a budget for next 12 months on your actual expenses for the past 12 months. You need to get your expense information into what is in effect.

Questions:

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  1. What are your information sources for this data warehouse?
  2. Describe how you would carry out each of the five steps of data preparation for a data warehouse, from extraction through summarization. If a particular step does not apply, say so and justify your statement.

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